APPROACHES TO ELIMINATING THE LIMITATIONS OF EXPERT SYSTEMS

Abstract

Expert systems have become essential tools for solving domain-specific problems by simulating expert decision-making through computer programs. However, their functionality is often restricted by challenges like limited knowledge acquisition, lack of flexibility, and computational inefficiencies. This paper investigates various strategies to address these issues, including leveraging automated knowledge extraction, adopting modular and hybrid architectures, and incorporating advanced user interfaces. Additionally, performance improvements are highlighted through graphical data and real-world case studies, demonstrating the practical implications of these approaches